Cameras, such as, but not limited to, consumer cameras (including video cameras), cell-phone cameras, and other conventional cameras employ certain camera settings designed to achieve some overall image quality. These camera settings, which may include aperture, gain, exposure, and other camera settings, have a significant influence on a quality of images acquired by a camera as well as subsequent processing of those images, for example, facial recognition, etc.
In some instances, conventional cameras employ face detection to assist the camera in adjusting these camera settings. However, these conventional cameras may sacrifice, for example, an exposure of a background (e.g., either underexposure or overexposure of the background) in favor of an exposure of the detected face. Such underexposure or overexposure of the background may result in the conventional camera failing to detect other faces in a scene. In addition, even if multiple faces are detected in the scene, such conventional cameras may have difficulty determining which detected face to use for adjusting the camera settings or difficulty generating camera settings sufficient for all faces.
The camera settings impact a quality of images acquired by the camera, which in turn, impact a performance of any subsequent image processing performed on the acquired images. Such image processing may include face detection, face recognition, or other computer vision algorithms. In some instances, a “quality” of the acquired images for purposes of face detection (or other image processing such as facial recognition) may differ from a “quality” of the acquired images for purposes of aesthetics (i.e., human perception of “image quality”).
What is needed is an improved system and method for intelligent camera control that enhances performance of subsequent image processing on acquired images.